Pengembangan E-LKPD Deep Learning Materi Gerak Lurus Berubah Beraturan pada Permainan Tradisional Oto Pering Manggarai

ADUR, Maria Felniani Purnasari (2026) Pengembangan E-LKPD Deep Learning Materi Gerak Lurus Berubah Beraturan pada Permainan Tradisional Oto Pering Manggarai. Undergraduate thesis, universitas katolik widya mandira.

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Abstract

This study aims to develop a deep learning–based E-Student Worksheet (E-LKPD) integrated with the traditional game Oto Pering of Manggarai as a learning context for the topic of Uniformly Accelerated Linear Motion (UARM), as well as to determine the product feasibility, improvement of learning outcomes, and students’ responses to the developed E-LKPD. This research employed a Research and Development (R&D) method using the ADDIE model, which consists of the Analysis, Design, Development, Implementation, and Evaluation stages. The research subjects were 30 seventh-grade students of class VII D at SMPK Adisucipto Penfui. The feasibility of the E-LKPD was analyzed through validity and reliability tests conducted by six validators, consisting of material experts and media experts. The results showed that the E-LKPD obtained an Aiken’s V value of 0.84 for the material aspect and 0.83 for the design aspect, indicating that the product required revisions based on the validators’ suggestions. Revisions were carried out by adding local cultural context to the material, improving the presentation of content, adjusting font size, and incorporating graphical features to support conceptual understanding. After the revisions, the E-LKPD was considered more aligned with the learning objectives and students’ characteristics. The reliability test results showed percentages of 82.2% for the material aspect and 76.5% for the design aspect, both of which fall into the very reliable category, indicating that the assessment instrument is consistent. The effectiveness of the ELKPD was analyzed through improvements in students’ learning outcomes using pretest and posttest scores. The results indicated an increase in the average score from 39.33 in the pretest to 82.00 in the posttest, with an N-Gain value of 0.7032, which is categorized as high. This demonstrates that the use of the E-LKPD is effective in improving students’ learning outcomes. In addition, students’ responses to the use of the E-LKPD reached a percentage of 84.916% in the very good category, indicating that the E-LKPD is interesting, easy to use, and suitable for learning needs. Based on the overall data analysis, the deep learning–based ELKPD integrated with the traditional Oto Pering game of Manggarai is considered to have good quality, is effective in improving learning outcomes, and receives positive responses from students, making it a potential learning medium for physics instruction at the junior high school level.

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